Formation Coordinated Control for UUVs Based on Position-Velocity Communication Topology

Unmanned Underwater Vehicle (UUV) is one of the systems that have a complex characteristic. UUV usually used to obtain data, mapping and underwater survey. One of a complexity that UUV have is based onuncertainty and non-linearity of hydrodynamics parameter. Besides that, UU V which studied in this paper have 6 degree of freedom, so it has also a lot parameter. And to handle that, a bigger system need to divide into some sub-system, the divided is based on control needed. To handle a movement of UUV, it’s important to build a control system that effective and efficient and a writer choose PID and Sliding-PID (SMC-PID) as a controller Modeling system used to linearize a non-linier system from UUV, linearizing around the equilibrium point. Then make a model into a state space, these state space uses for a controlling. For a control system building and respond system from an UUV movement, MATLAB program is needed Keywords: UUV, PID control, Sliding-PID, MATLAB Simulink, Linier System

Unmanned underwater vehicles (UUVs) have become increasingly popular in recent years due to their use in various applications. The motivations for using UUVs include the exploration of difficult and dangerous underwater environments, military tasks in mine detection, intelligence gathering and surveillance, the inspection of offshore oil and gas infrastructure in the oil and gas industry, scientific research for studying marine life, and the search and rescue of missing persons or submerged airplanes or boats in underwater environments. UUVs offer many advantages in achieving the desired applications with increased safety, efficiency, and cost-effectiveness. However, there are also several challenges associated with their communication, navigation, power requirements, maintenance, and payload limitations. These types of vehicles are also prone to various disturbances caused by currents of the ocean, propulsion systems, and unmolded uncertainties. Practically, it is a challenging task to design a controller that will ensure optimal performance under these conditions. Therefore, the control system design is of prime importance in the overall development of UUVs. Also, the UUV controller receives input from different sensors, and the data from these sensors are used by the controller to perform different tasks. The control systems of UUVs should take into account all uncertainties and make them stable so that all sensors can perform optimally. This paper presents a complete review of different control system design algorithms for UUVs. The basic logic designs of several control system algorithms are also presented. A comparison is made based on reliability, robustness, precession, and the ability of the controller to handle the nonlinearity that is faced by UUVs during their missions. Simulation and experimental results are thoroughly studied to gain insight into each algorithm. The advantages and disadvantages of each algorithm are also presented, which will facilitate the selection of a suitable algorithm for the control system design of UUVs.

Focusing on coordination and consensus, this paper, addresses a control problem for a group of unmanned underwater vehicles (UUVs) by tracking a maneuvering target with varying velocity and time delays. To realize coordinated target tracking, consensus control of multiple UUVs requires neighboring UUV state information, detected target state information, and estimated target acceleration information. At least one UUV is assumed to be capable of obtaining information about the target, and the communication topology graph of the vehicle is assumed to be undirected connected. We consider the convergence analysis of this multi-UUV system for two conditions: information interaction between the target and an UUV with time delays and information interaction between the target and an UUV without time delays. Sufficient conditions for the uniform ultimate boundedness of the tracking errors and estimation errors are obtained by utilizing a Lyapnov-Krasovskii functional. Two simulations are presented to demonstrate the effectiveness of the proposed method.

Unmanned underwater vehicle (UUV) has been applied for civil field all over the world. In technologies of UUV, the underwater recovery technology plays an essential part. And the superior precision control system is necessary for UUV underwater recovery. In this paper, the research background is the mother ship carries UUV recycling in piggyback method. And the important point is the method of dynamic positioning to line in process of UUV recovery and the UUV dynamic positioning to line strategy based on the robust model predictive control algorithm is proposed. Then, a digital simulation is made to verify the feasibility of the control algorithm. Through the simulation results, the conclusion of control algorithm is got.

In this paper, an adaptive robust PD controller for Unmanned Underwater Vehicle (UUV) is proposed. Though conventional PD control is simple and effective for UUV heading control, in many circumstances, a large initial torque is required, while the maximum torque of the rudder is limited, thus making it unavailable to further improve the heading control effects. The adaptability and robustness of this control system is investigated by computer simulation, lake and sea trials. Experimental results indicate the effectiveness of the proposed controller in dealing with model uncertainties, nonlinearities of UUV, and eliminating the excessive initial output torque of the rudder and environmental disturbance caused by sea currents and waves.

Unmanned underwater vehicles require a hull resistant to immersion and, therefore, to hydrostatic pressure, which places high demands on its design, manufacture and inspection, where dimensional control is a fundamental part of the verification of the shapes of the structure. In this research, a comparison is made of the dimensional control techniques currently used for the naval sector and their viability in the field of unmanned underwater vehicles. A cylindrical body steel model will be measured, with the characteristic dimensions of the unmanned underwater vehicles, executing tests using three measurement techniques, such as the optical measurement of surface points, the surface probing technology and the surface laser scanner with large volume of points. Experimental data will be provided in terms of mean diameter of the sections that make up the hull, defect of circularity and position of the optimum centre, which will lead to the development of a guide of good practices for selecting and using each technique depending on the requirements and demands of the unmanned underwater vehicle under study.

This paper addresses the problem of guidance of unmanned underwater vehicles (UUVs). In the framework of a two layered hierarchical architecture decoupling the system dynamics and kinematics, two guidance laws for approaching a target with the desired orientation and following an environmental feature have been designed with Lyapunov-based techniques. Suitable acoustic-based estimators of the corresponding operational variables have been designed and integrated with the guidance and control system. Experimental results of pool trials of a prototype UUV executing free-space maneuvering and wall-following tasks are reported and discussed.

Due to their utility in replacing workers in tasks unsuitable for humans, unmanned underwater vehicles (UUVs) have become increasingly common tools in the fish farming industry. However, earlier studies and anecdotal evidence from farmers imply that farmed fish tend to move away from and avoid intrusive objects such as vehicles that are deployed and operated inside net pens. Such responses could imply a discomfort associated with the intrusive objects, which, in turn, can lead to stress and impaired welfare in the fish. To prevent this, vehicles and their control systems should be designed to automatically adjust operations when they perceive that they are repelling the fish. A necessary first step in this direction is to develop on-vehicle observation systems for assessing object/vehicle–fish distances in real-time settings that can provide inputs to the control algorithms. Due to their small size and low weight, modern cameras are ideal for this purpose. Moreover, the ongoing rapid developments within deep learning methods are enabling the use of increasingly sophisticated methods for analyzing footage from cameras. To explore this potential, we developed three new pipelines for the automated assessment of fish–camera distances in video and images. These methods were complemented using a recently published method, yielding four pipelines in total, namely, SegmentDepth, BBoxDepth, and SuperGlue that were based on stereo-vision and DepthAnything that was monocular. The overall performance was investigated using field data by comparing the fish–object distances obtained from the methods with those measured using a sonar. The four methods were then benchmarked by comparing the number of objects detected and the quality and overall accuracy of the stereo matches (only stereo-based methods). SegmentDepth, DepthAnything, and SuperGlue performed well in comparison with the sonar data, yielding mean absolute errors (MAE) of 0.205 m (95% CI: 0.050–0.360), 0.412 m (95% CI: 0.148–0.676), and 0.187 m (95% CI: 0.073–0.300), respectively, and were integrated into the Robot Operating System (ROS2) framework to enable real-time application in fish behavior identification and the control of robotic vehicles such as UUVs.

The problem of constructing a control system for underwater vehicles is relevant due to the growing scope of their application, including acting in autonomous modes. Moreover, it is required to have an ability to use these devices both in quasi-stationary and close to pulsed mode. Thus, it is necessary to develop a mathematical model of vehicle’s dynamics for autonomous operations of an unmanned underwater vehicle (UUV), which would describe the dynamics of motion as close as possible to the real one. The current paper is denoted to the identification problem of UUV model. A comparative analysis of UUV dynamics models was carries out, among which a model that uses added masses of liquid to describe hydrodynamic forces was selected. For UUV of a symmetrical streamlined shape with a small displacement and performing plane movements, it is assumed that the influence of the attached fluid manifests itself in the form of an increase in mass and moments of inertia. A control system designed to stabilize the device was built on the model, after which it was adjusted on the existing sample of the UUV. The considered theoretical and experimental methods for identifying the dynamic model of the UUV turned out to be competitive with each other and gave comparable results for calculating the added masses. The carried out full-scale experiments confirms that the proposed method for estimating the added masses is quite effective for constructing a control system designed to operate in a given motion mode.

Underwater Wireless Sensor Network (UWSN) is a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in area of underwater wireless sensor networks have also been discussed.

Unmanned Underwater Vehicles (UUVs) can be utilized to perform difficult tasks in cluttered environments such as harbor and port protection. However, since UUVs have nonlinear and highly coupled dynamics, motion planning and control can be difficult when completing complex tasks. Introducing models into the motion planning process can produce paths the vehicle can feasibly traverse. As a result, Sampling-Based Model Predictive Control (SBMPC) is proposed to simultaneously generate control inputs and system trajectories for an autonomous underwater vehicle (AUV). The algorithm combines the benefits of sampling-based motion planning with model predictive control (MPC) while avoiding some of the major pitfalls facing both traditional sampling-based planning algorithms and traditional MPC. The method is based on sampling (i.e., discretizing) the input space at each sample period and implementing a goal-directed optimization (e.g., A*) in place of standard numerical optimization. This formulation of MPC readily applies to nonlinear systems and avoids the local minima which can cause a vehicle to become immobilized behind obstacles. The SBMPC algorithm is applied to an AUV in a 2D cluttered environment and an AUV in a common local minima problem. The algorithm is then used on a full kinematic model to demonstrate the benefits.

Unmanned Underwater Vehicles (UUVs) can be utilized to perform difficult tasks in cluttered environments such as harbor and port protection. However, since UUVs have nonlinear and highly coupled dynamics, motion planning and control can be difficult when completing complex tasks. Introducing models into the motion planning process can produce paths the vehicle can feasibly traverse. As a result, Sampling-Based Model Predictive Control (SBMPC) is proposed to simultaneously generate control inputs and system trajectories for an autonomous underwater vehicle (AUV). The algorithm combines the benefits of sampling-based motion planning with model predictive control (MPC) while avoiding some of the major pitfalls facing both traditional sampling-based planning algorithms and traditional MPC. The method is based on sampling (i.e., discretizing) the input space at each sample period and implementing a goal-directed optimization (e.g., A*) in place of standard numerical optimization. This formulation of MPC readily applies to nonlinear systems and avoids the local minima which can cause a vehicle to become immobilized behind obstacles. The SBMPC algorithm is applied to an AUV in a cluttered environment and an AUV in a common local minima problem.

*Agency for Defence Development, Jinhae, Korea**Graduate School of Korea Maritime University, Busan, Korea***Department of Ocean Engineering, Korea Maritime University, Busan, KoreaKEY WORDS: Cylindrical shell 원통형 구조물, High frequency vibration 고주파 진동, Excitation 가진, Noise 소음, Underwater vehicle 수중운동체ABSTRACT: Underwater vehicles such as UUVs (Unmanned Underwater Vehicles) and ROVs (Remotely Operated Vehicles) use sonar to detect their underwater environment or other underwater vehicles. The underwater vehicles designed recently have an electrical power system with high rotational speed. This system can generate high frequency vibra tions above 10 kHz, and these vibrations can cause bad (negativ e) effects on the performance of the sonar. In many previous investigations, nume rical analyses have been used for high frequency vibration prob lems. In this study, an experimental analysis was carried out, and a circular cylind rical shell was considered as the hull structure of an underwat er vehicle. Frequency transfer functions for the circular cylindrical shell were iden tified using an experimental vibration analysis in the air and in a fully-submerged condition. We compare the frequency transfer functions in the a ir and water to obtain hydro-elastic effects. It is found that the dynamic characteristics of the circular cylindrical shell are changed b y varying the response position.교신저자 박한일: 부산광역시 영도구 동삼 2동, 051-410-4326, hipark@hhu.ac.kr본 연구는 20011년 6월 개최된 한국해양과학기술협의회 공동학술대회에 발표된 논문을 근간으로 하고 있음을 밝힙니다 .

A consensus algorithm proposed in the paper is applied to tackle remarkable problems of unmeasurable velocities, the environmental disturbances, and the limited communication environment for the multiple unmanned underwater vehicles (multi-UUVs). Firstly, for a complex nonlinear and coupled model of the unmanned underwater vehicle (UUV), a technique of feedback linearization is developed to transform the nonlinear UUV model into a second-order integral UUV model. Secondly, to address the problem of the unavailable velocity information and environmental disturbances for the multi-UUVs system, we design a distributed extended state observer (DESO) to estimate the unmeasurable velocities and environmental disturbances using the relative position information. Finally, we propose a protocol based on the estimation information from the DESO and demonstrate that the multi-UUVs system with the switching directed topologies under the protocol can reach consensus asymptotically. The theoretical result proposed in the literature is verified by one numerical example.

Experimental testing of a cooperative ASV-ROV multi-agent system